Short communication. Effects of antibiotics (oxytetracycline, florfenicol or tulathromycin) on neonatal calves’ faecal microbial diversity.

In this study, we used barcoded pyrosequencing of the 16S rRNA gene to characterise the effects of antibiotic treatment upon the faecal microbiota of neonatal calves. Eleven pre-weaned calves were treated for pneumonia or otitis using one of three antibiotics (oxytetracycline, florfenicol or tulathromycin) and were matched for age /date of birth and sex with eleven control calves. All calves were born and reared at the same farm. Faecal microbial diversity data were obtained by barcoded pyrosequencing of the 16S rRNA gene one week pre-treatment, and one and two weeks post treatment for both treated and control calves. Using multivariate discriminant analysis we were able to show that antibiotic treatment has a substantial effect on faecal samples’ microbial composition one week after administration; this effect was no longer observed two weeks after administration. The effect of oxytetracycline treatment on Lactobacillus spp. was shown to be significant but many other important species appeared to be unaffected. The small number of calves used in the study prohibited quantitative comparisons of the effects of individual antibiotics compared to others on Chao1 richness index; despite this, however, some interesting numerical differences were apparent. In conclusion, our study serves to illustrate that change occurs in the gut microbiome of the young ruminant in response to antimicrobial administration. Given the limitations of our study we suggest that further similar studies are necessary

Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study

Background A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. Methods Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening. Results About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95–100) to 100% and specificity from 99% (95% CI 97–100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76–87) to 94% (95% CI 89–98) and specificity ranging from 76% (95% CI 70–82) to 92% (95% CI 88–96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only. Conclusions People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people